International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 63 - Issue 21 |
Published: February 2013 |
Authors: S. Anbumalar, R. Anandanatarajan, P. Rameshbabu |
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S. Anbumalar, R. Anandanatarajan, P. Rameshbabu . Sparse Non-negative Matrix Factorization and its Application in Overlapped Chromatograms Separation. International Journal of Computer Applications. 63, 21 (February 2013), 1-10. DOI=10.5120/10587-5199
@article{ 10.5120/10587-5199, author = { S. Anbumalar,R. Anandanatarajan,P. Rameshbabu }, title = { Sparse Non-negative Matrix Factorization and its Application in Overlapped Chromatograms Separation }, journal = { International Journal of Computer Applications }, year = { 2013 }, volume = { 63 }, number = { 21 }, pages = { 1-10 }, doi = { 10.5120/10587-5199 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2013 %A S. Anbumalar %A R. Anandanatarajan %A P. Rameshbabu %T Sparse Non-negative Matrix Factorization and its Application in Overlapped Chromatograms Separation%T %J International Journal of Computer Applications %V 63 %N 21 %P 1-10 %R 10.5120/10587-5199 %I Foundation of Computer Science (FCS), NY, USA
A new NMF algorithm has been proposed for the deconvolution of overlapping chromatograms of chemical mixture. Most of the NMF algorithms used so far for chromatogram separation do not converge to a stable limit point. To get same results for all the runs, instead of random initialization, three different initialization methods have been used namely, ALS-NMF (robust initialization), NNDSVD based initialization and EFA based initializations. To improve the convergence, a new sNMF algorithm with modified multiplicative update (ML-sNMF) has been proposed in this work for overlapped chromatogram separation. The algorithm has been validated with the help of simulated partially, severely overlapped and embedded chromatograms. The proposed ML-sNMF algorithm has also been validated with the help of experimental overlapping chromatograms obtained using Gas Chromatography –Flame Ionization Detector (GC-FID) for the chemical mixture of acetone and acrolein.